Evaluating the contribution of bank-specific variables in the cost efficiency of the Jordanian banks

This paper examines the cost efficiency of seventeen Jordanian banks during the period of financial deregulation, 1996-2007. This paper follows a two-stage approach. In the first stage, cost efficiency scores are computed using an input-oriented data envelopment analysis (DEA). At the second stage, cost efficiency scores are regressed on a set of potential explanatory variables in a logit model. While the cost efficiency scores show a declining trend during the early and middle phase of deregulation, they show large improvements in the final phase of financial deregulation. Over the entire sample period, cost efficiency has increased at the rate of 1.55% per annum; the improvement in allocative efficiency has contributed about 60% of this. In this sample I find that bank size, loan to deposit ratio and good management practises positively affects banks cost efficiency and return on equity and number of bank branches negatively affect bank cost efficiency.

Scienpress Ltd, 2015

Evaluating the contribution of Bank-specific variables in

the Cost Efficiency of the Jordanian Banks

Ammar Jreisat 1

Abstract

This paper examines the cost efficiency of seventeen Jordanian banks during the period of financial deregulation, 1996-2007 This paper follows a two-stage approach In the first stage, cost efficiency scores are computed using an input-oriented data envelopment analysis (DEA) At the second stage, cost efficiency scores are regressed on a set of potential explanatory variables in a logit model While the cost efficiency scores show a declining trend during the early and middle phase of deregulation, they show large improvements in the final phase of financial deregulation Over the entire sample period, cost efficiency has increased at the rate of 1.55% per annum; the improvement in allocative efficiency has contributed about 60% of this In this sample I find that bank size, loan to deposit ratio and good management practises positively affects banks cost efficiency and

return on equity and number of bank branches negatively affect bank cost efficiency

JEL classification numbers: D22, D24, D61 and G21

Keywords: Cost Efficiency, Deregulation, Two-stage Data Envelopment Analysis,

Jordanian Banks

1 Introduction

There is an enormous body of literature on measuring banking efficiency in the Western economies The studies of banking efficiency for the Middle East economies are few The reasons for this can be attributed to two factors First, the financial systems of many Middle Eastern countries are highly regulated and outdated They are dominated by the public sector and do not face much competition Second, reliable data on banks are not available for many countries However, during the last fifteen years, many Middle East economies

1 Dr., Assistant Professor of Finance, Department of Banking and Finance, College of Business Administration, AL Ain University of Science and Technology, Abu Dhabi, UAE

Article Info: Received : February 14, 2015 Revised : March 15, 2015

Published online : July 1, 2015

have gradually moved towards liberalising their financial systems This has encouraged researchers to undertake studies of banking efficiency and productivity in some of the countries, see, for example, Hassan et al (2004) for Bahrain and Al-Muharrami (2007) for GCC countries The efficiency is a vital factor for financial institutions wishing to carry out their business successfully, given the increasing competition in the financial markets Moreover, in a rapidly changing and more globalised financial marketplace, governments, regulators, managers and investors are concerned about how efficiently banks transform their expensive inputs into various financial products and services

The present study examines the cost efficiency of banks operating in Jordon during the period of financial deregulation, 1996–2007 Jordan represents an example of a successful transformation from a highly regulated regime to a deregulated economy Before the 1980s, the Jordanian banking sector was highly regulated, and economic policies were directed towards protecting them from foreign competition The financial authorities put in place measures to limit foreign entry As a result, domestic banks in Jordan operated in an oligopolistic environment (Bdour and Al-khoury, 2008) In 1989, Jordan experienced a crisis in its banking system following the collapse of Petra Bank and the financial difficulties of six other financial institutions linked to it The crisis was a result, among other factors, of inappropriate banking regulations, over-exposure of the banking system to the real estate market and imprudent speculations in foreign exchange (Canakci, 1995) The 1989 crisis led to closer cooperation between the government of Jordan, the International Monetary Fund (IMF) and the World Bank in order to develop the Jordanian banking sector and to initiate a reform program The government took various steps to enhance system efficiencies and to create competition among banks The reform program consisted of removing restrictions on interest rates, reducing direct governmental lending, promoting deregulation and reducing restrictions on foreign exchange transactions and on the movement of capital In addition, the government adopted trade liberalisation policies

to enhance economic growth and promote exports (Maghyereh, 2004; Central Bank of Jordan, 2005)

This study focuses on the measurement of cost efficiency in seventeen Jordanian banks during the period of financial deregulation, 1996–2007 The paper sample consists of fourteen domestic (two large, eight medium and four small) and three foreign banks for which required data are available These banks cover close to 90 per cent of banking output

in Jordon (Association of Banks in Jordan, 2007)

One of the earliest studies of technical efficiency in the Jordanian banking sector was Al-Shammari and Salimi’s (1998) In this study, DEA was used and an input oriented model was applied to 16 out of 18 commercial banks operating in Jordan in the period 1991–1994 The dataset for the study was obtained from the Amman Financial Market (1995) The empirical results revealed that the majority of banks investigated were fairly technically inefficient over the study period Maghyereh (2004) investigated total factor productivity (TFP) in eight domestic Jordanian banks over 18 years from 1984 to 2001 The DEA model used three inputs (labour, capital, and deposits) and three outputs (earning assets, loans and liquid assets and investments) The results indicated that the mean of technical efficiency for all banks over the sample period was 91.8 The main source of technical inefficiency in the Jordanian banks was scale inefficiency, with an average rate of 93.1%, which means the inefficiency due to the divergence of the actual scale of operation for the most productive scale size is 6.9% also, the average pure technical efficiency is 96%, which means that banks could produced the same amount of outputs with only 4% fewer inputs

Importantly, the result indicated that the larger banks in the sample had lower scale efficiency and higher pure technical efficiency than small and medium banks

Isik et al (2004) analysed managerial2 and scale efficiencies in the Jordanian banking sector (17 commercial, investment and Islamic banks) operating in Jordan over 1996–2001 They used two DEA Models The first applied the production approach and specified banks as multi-product firms producing credits, investment securities and deposits services by employing labour and capital; the second model took an intermediation approach which defined banks as financial intermediaries where labour, capital and deposits served as inputs, and credits and investments securities served as outputs The results indicated that Jordanian banks would obtain significant cost savings (as much as 40%) should they catch

up with the best practice banks The findings from the first model (production approach) estimated managerial efficiency at 71%, pure technical efficiency at 89% and scale efficiency at 79%; from the second model (intermediation approach) the managerial efficiency, pure technical efficiency and scale efficiency turned out to be 89%, 96% and 92% respectively Most of the managerial inefficiency was found to be due to scale inefficiency rather than pure technical inefficiency The study also found that most banks

in Jordan experienced increasing returns to scale in their operations under both models, suggesting that the Jordanian banks could have expanded their operations by either internal

or external growth The Arab Bank was found to be most efficient bank

Bdour and Al–Khoury (2008) evaluated the technical efficiency of 17 domestic commercial Jordanian banks during the liberalisation period, 1998–2004 The study used DEA with an intermediation approach, with three inputs (net-operating expenses, total assets and number

of employees) and three outputs (net operating income, demand deposits, and net direct credits) They found that the liberalisation program had improved the efficiency of the Jordanian banks for all years except 2003 and 2004, when a decline in efficiency occurred, possibly due to the adverse effects of the Gulf War The average technical efficiency score during the period 1998-2004 were (53.09%, 96.36%, 98.77%, 98.38%, 99.03%, 89.42%, and 83.36%) respectively

Recently, Paul & Jreisat (2012) investigated the level of cost efficiency in 17 Jordanian banks during the period 1996-2007 in which financial deregulation took place However, this paper continues to Paul & Jreisat (2012) uses second stage, Cost efficiency scores are regressed on a set of potential explanatory variables in a logit model Firstly, uses a DEA based approach, where input-oriented model is employed in order to examine cost efficiency in the Jordanian banking sector spanning the entire deregulated period:

1996-2007 I adopt two-stage approach, in which cost efficiency scores for the sample under study are estimated in the first stage Further in the first stage, the cost efficiency scores were decomposed into the product of allocative and technical efficiency Finally, in the second stage I study the potential determinants of cost efficiency

The paper is organised as follows Section 2 discusses the concept of cost efficiency and its estimation based on DEA approach Section 3 discusses the data as well as input and output variables The results on banking cost efficiencies are discussed in Section 4 Determinants

of banks efficiency and the related estimation results are presented in Section 5 Section 6 presents some conclusions

2 Managerial inefficiency consists of two mutually exclusive and exhaustive components, firstly, pure technical inefficiency

2 The Cost Efficiency: Concept and Measurement

A bank is considered cost efficient if it can find a combination of inputs that enables it to produce the desired (given) outputs at the minimum cost The cost efficiency (CE) is the product of technical and allocative efficiencies A firm/bank is considered technically efficient if it is not possible to reduce the level of inputs to produce a given level of output

To put in other words, the existence of technical inefficiency would mean that some inputs can be reduced without affecting the level of output The allocative efficiency (AE) refers

to the selection of inputs to produce a certain level of outputs at given input prices such that the cost of production is minimum Cost efficiency is defined as the ratio of minimum (optimum) cost to the observed cost for producing a level of output by a firm If the cost efficiency score for a firm is 0.75, then it would mean that the bank could have achieved the same level of output with 75 % of its costs In other words, the firm wastes 25% of its costs relative to the best-practice firm (Berger and Mester, 1997)

Figure 1, reproduced from Coelli et al (2005, p 52), explains how cost efficiency can be conceptualised and measured using input-oriented framework Following the lead of Farrell (1957), I consider a simple example of a bank requiring two inputs x1 and x2 for producing

one output q, assuming constant return to scale Let w refer to input price vector and x to the observed vector of inputs used associated with point P; and let xˆ and x*refer to the input vectors associated with the technically efficient point Q and the cost minimising input vector at Q respectively Thus, cost efficiency can be defined as the ratio of input costs associated with input vectorsx and x* associated with pointsPandQ

(1)

/ x w x w * OP OR CE     (1)

Source: Coelli et al (2005) Figure 1: Cost, Technical and Allocative Efficiencies

As shown in Figure 1, the slope of the isocost lineA A represents the proportion of input prices AE and TE can be calculated as follows:

OR







xˆ

w

x

(2)

OP

OQ







x

w

xˆ

w

(3)

Thus, if the firm sets its inputs at the point Q on the unit isoquant curve S, then it can

be said that this firm is technically efficient but allocatively inefficient If the firm wishes

to be technically and allocatively efficient it should reduce the production cost represented

by the distance RQ, which would occur at the allocatively (and technically) efficient point

Q, instead of at the technically efficient but allocatively inefficient point Q

It follows from this that cost efficiency can be expressed as the product of technical and allocative efficiency measures:

) / ( ) / ( ) /

AE

TE     (4)

DEA efficiency scores assign numerical values (between 0 and 1 or 0 and 100%) to the cost efficiency level of a DMU relative to others Cost efficiency (CE) of one represents a fully cost efficient bank; (1-CE) represents the amount by which the bank could reduce its costs and still produce at least the same amount of output

To measure CE, two sets of linear programs are required, one to measure technical efficiency and the other to measure cost efficiency The cost efficiency is often called economic efficiency or overall efficiency The details of linear programming required to estimate cost efficiency is provided in Coelli et al (2005, p.184) and hence is not repeated here

3 The Data and Variables

There is no agreement among economists on the choice of bank inputs and outputs required for estimating DEA model; in fact, the choice of input and output variables for the banking sector remains controversial In the literature, I come across three distinct approaches for selecting inputs and outputs: the production approach, the intermediation approach, and the value-added approach The first approach views financial institutions as producers who use inputs of labour and capital to generate outputs of deposits and loans This approach is used

by Sathye (2001), Neal (2004) and many others The intermediation approach views financial institutions as intermediaries that convert and transfer financial assets from surplus units to deficit units Ahmad (2000) views banks as intermediaries and uses two inputs, labour and deposits; and two outputs, total loans and other investments, for measuring efficiency in Jordanian banks during 1990–1996 In another conceptualisation

of the intermediation approach, Paul and Kourouche (2008) and Kourouche (2008) use interest expenses and non-interest expenses as inputs and interest income and non-interest income as outputs In the value-added approach, high-value-creating activities such as making loans and taking deposits are classified as outputs, whereas labour, physical capital and purchased funds are classified as inputs (Wheelock and Wilson, 1995)

The intermediation approach is quite popular in empirical research particularly that based

on cross-sectional data (Colwell and Davis, 1992; Favero and Papi, 1995) The production approach is known to have a limitation in that it excludes interest expenses, which are considered a vital part of banking

There are other practical issues or reasoning governing the selection of inputs and outputs

If one’s aim is to estimate a unit’s production efficiency, then the production approach might be appropriate However, if the interest of the researcher lies in examining intermediation efficiency, then the intermediary approach is more appropriate The choice

of variables may also depend on the availability of data

Following intermediation approach, I choose two inputs, labour (x1) and total deposits (x2) and their prices and two outputs, total loans (y1) and other investments (y2) Labour is

measured in terms of full time workers; total deposits are the total amount of customers’

deposits Total loans are the total credit facilities as they appear in the balance sheets of the banks Other investments consist of investments in bonds and securities, shares, treasury bills, and investment in affiliate and subsidiary companies The price of labour is obtained as: wages and personal expenses and benefits of employees divided by number of employees The price of funds is obtained as: interest expenses divided by total deposits All the monetary variables are expressed in 2000 Jordanian Dinar (JD) using GDP deflator Ideally an investment price deflator should have been used to express other investments at constant prices Since information on investment deflators is not available, I use a GDP deflator to express investment at constant price This adjustment does not apply to labour,

as this is measured by the number of employees (workers)

The data are collected for 17 banks, out of these 14 are domestic and 3 are foreign banks The data for domestic banks (listed on the Amman Stock Exchange) are collected from the Annual Reports of individual banks and the Central bank of Jordon The foreign banks are not listed on the Amman Stock Exchange Hence I had to collect data for them from libraries and the Association of Banks in Jordan

For a comprehensive analysis, the domestic banks are classified into three categories, based

on their assets size (measured in Jordanian Dinar) in 2007: (i) Large domestic banks (Assets size ≥ JD 4000 million), (ii) Medium domestic banks (700 ≤ Assets size < JD 4000 million), and (iii) Small domestic banks (Assets size < JD 700 million) The banks’ assets have changed over the years but this has not changed their classification, facilitating their comparison over the sample period The banks are listed in Table 1

Table 1: Assets of Domestic and Foreign Banks, 2007 Bank

Category

Name

Total Assets (JD millions) Domestic

The Housing Bank for Trade and

Finance

HBTF 4132.6

Jordan Islamic Bank For Finance and

Investment

JIBF 1596.83

Union Bank for Saving and

Investment

Jordan Investment and Finance Bank JIFB 707.37

Societe Generale De Banque-Jordanie SGBJ 222.58

Source: The Association of Banks in Jordan, Annual Report 2007

A summary of statistics on outputs, inputs and input prices for different categories of banks

is provided in Table 2 A few interesting points emerge from the table First, the number

of employees in large banks is almost three times the number in medium sized banks, six times the number in small banks and twelve times the number in foreign banks The number

of employees within the domestic banks as a whole is five times that of the number within foreign banks Also, the deposits in the large Jordanian banks are almost eleven times of those held by medium banks, and thirty two times of those of small banks

Second, the total loans extended to the customers by Jordanian banks of all sizes are about half of that total deposits In light of this, it can be inferred that Jordanian banks are facing

a risky business environment and so they may be reluctant to engage heavily in loan markets, as business credits are more costly to originate, maintain and monitor The total loans provided by domestic banks to customers are seven times larger than those provided

by foreign banks Other investments of domestic banks are twenty six times larger than those of foreign banks,

Third, all input and output variables are more volatile for large banks compared the medium and small banks The standard deviations of all variables for the large banks are larger than

the medium and small banks, and the large banks have the smallest minimum and largest maximum

4 Empirical Results on Cost Efficiency

The cost efficiency scores of banks are obtained by running an input-oriented DEA model using the software package, DEAP Version 2.1 (Coelli, 1996) While the bank specific yearly scores are presented in Appendix Table A1, Table 4 presents the annual efficiency scores for the banking sector as a whole The latter are the weighted geometric mean of bank-specific scores where their shares in total output serve as weights The cost efficiency score was low (55.4%) in the beginning of the sample period The efficiency scores show

a declining trend with some fluctuations up to 2003 and an improvement thereafter, showing the highest cost efficiency score of 66.5% in the final year (2007) of the sample period The estimates of allocative efficiency are higher than the technical efficiency in each year, see Fig 1

Table 2: Summary Statistics for the Variables for the Jordanian Banks 1996–2007

Large Banks

Total Loans 3163.35 2491.00 556.61 7867.51

Other Investments 1444.36 1310.84 129.18 4019.06

Total Deposits

Price of Labour

Price of Fund

6871.50

32557 0.0384

5439.22

21368 0.0152

976.81

5519 0.0120

13845.15

63685 0.0589 Medium Banks

Total Loans 292.18 173.88 11.39 898.26

Other Investments 86.13 51.58 3.19 205.16

Total Deposits

Price of Labour

Price of Fund

597.96

10573 0.0430

354.63

4331 0.0198

14.20

4849 0.0118

1381.49

24493 0.0860 Small Banks

Total Loans 106.97 59.42 21.03 234.98

Other Investments 29.95 32.10 0.31 113.54

Total Deposits

Price of Labour

Price of Fund

210.62

10184 0.0478

106.56

3652 0.0193

36.36

4526 0.0165

387.01

25304 0.0888 Foreign Banks

Total Loans 92.46 52.29 14.17 203.04

Other Investments 10.08 6.47 0.20 30.95

Total Deposits 236.66 97.32 93.34 442.33

Price of Labour

Price of Fund

17945 0.0309

6305 0.0164

9213 0.0053

39297 0.0562

Note: SD: standard deviation Total loans, total deposits and other investments are

expressed in Jordanian Dinar (millions) at constant 2000 prices and labour is the number

of employees

Table 3: Estimates of Cost, Allocative and Technical Efficiencies, Jordanian Banking

Sector, 1996–2007

Figure 2: Technical, Allocative and Cost Efficiency Scores, 1996–2007

The sample period mean estimates of cost, allocative and technical efficiencies for the banking sector as a whole as well as for each bank category are presented in Table 4 The cost efficiency score of banks is 0.74, which implies that the banking sector could have reduced the cost of production by 26 percent without affecting the level of output In other words, banks have wasted 26 percent of resources in producing their levels of output The allocative efficiency is quite high (90%) This is consistent with the estimates reported for banks in most of the countries The group of large banks is found to be most efficient in

terms of cost efficiency as well as in terms of allocative and technical efficiencies The group of small banks ranks second in terms of their efficiency The cost efficiency of foreign banks is found to be the lowest (46%) The time series estimates of the cost efficiency by bank categories presented in Table 5 also reveal that the group of domestic banks has performed better than foreign banks in terms of CE and TE in each year of the sample period The gap in their efficiency levels has widened, especially from 2000 onwards The allocative efficiency of foreign banks is higher than the domestic banks This implies that in terms of input use in response to input prices, the foreign banks are more efficient than their domestic counterparts The group of large banks has outperformed all other bank categories in terms of cost efficiency in almost all the sample years

Table 4: Sample Period Mean Estimates of Cost, Allocative and Technical Efficiencies

All Domestic Banks 0.749 0.905 0.823

Note: CE: cost efficiency; AE: allocative efficiency; TE: technical efficiency

Table 5: Estimates of Cost Efficiency by Category of Banks and ownership, 1996–2007

Banks Efficiency 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Mean

Domestic Banks

Large

CE 0.798 0.824 0.811 0.778 0.828 0.864 0.918 0.830 0.938 0.900 0.920 0.965 0.863

AE 0.906 0.907 0.918 0.934 0.894 0.901 0.936 0.915 0.944 0.949 0.951 0.976 0.927

TE 0.882 0.908 0.885 0.833 0.927 0.959 0.981 0.907 0.993 0.949 0.967 0.989 0.930 Medium

CE 0.502 0.513 0.502 0.526 0.433 0.469 0.416 0.400 0.433 0.552 0.639 0.620 0.495

AE 0.745 0.857 0.780 0.858 0.873 0.881 0.854 0.851 0.818 0.848 0.897 0.926 0.848

TE 0.674 0.599 0.643 0.614 0.496 0.532 0.488 0.470 0.529 0.651 0.712 0.669 0.584 Small

CE 0.512 0.477 0.507 0.491 0.577 0.553 0.493 0.439 0.473 0.550 0.650 0.667 0.528

AE 0.849 0.865 0.882 0.899 0.910 0.892 0.839 0.788 0.746 0.821 0.908 0.913 0.858

TE 0.603 0.551 0.575 0.546 0.634 0.620 0.587 0.558 0.634 0.670 0.716 0.730 0.616

Foreign Banks

CE 0.485 0.571 0.561 0.521 0.390 0.392 0.386 0.409 0.435 0.444 0.458 0.517 0.460

AE 0.920 0.934 0.936 0.935 0.886 0.804 0.851 0.873 0.907 0.931 0.947 0.939 0.904

TE 0.527 0.612 0.599 0.557 0.440 0.487 0.454 0.468 0.480 0.477 0.484 0.550 0.508

All Domestic Banks

CE 0.709 0.727 0.713 0.696 0.714 0.744 0.760 0.695 0.774 0.772 0.815 0.841 0.749

AE 0.866 0.894 0.882 0.914 0.890 0.896 0.915 0.897 0.907 0.915 0.933 0.959 0.905

TE 0.819 0.813 0.808 0.761 0.802 0.830 0.831 0.775 0.853 0.844 0.873 0.876 0.823

ALL Banks

CE 0.700 0.721 0.707 0.689 0.704 0.736 0.750 0.687 0.765 0.764 0.805 0.831 0.737

AE 0.868 0.896 0.884 0.915 0.890 0.895 0.913 0.896 0.907 0.915 0.933 0.958 0.906

TE 0.807 0.805 0.800 0.753 0.791 0.822 0.822 0.767 0.843 0.835 0.863 0.867 0.814

Note: CE: cost efficiency; AE: allocative efficiency; TE: technical efficiency

To understand how efficiency has changed over the sub-periods of financial reforms and how changes in allocative and technical efficiencies have contributed to it, I decompose the growth of cost efficiency as the sum of the growth of allocative and technical efficiencies using the relationship AE ×TE = CE (see equation 5) The decomposition estimates for broad categories of banks for the full period under study as well as three sub-periods 1996–

99, 1999–03 and 2003–07, are presented in Table 7 These sub-periods represent the early, medium and later phases of financial deregulation/ reform in Jordanian economy